Bioaccumulation of heavy metals in different fishes of Gangetic river system in Varanasi and its health risk assessment

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Gautam, V. N. Mishra This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2168987/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Heavy metal load is one of the factor causing deterioration of water quality of rivers and anthropogenic activities being the major cause. Present article is an attempt to evaluate the potential human health risks posed by four heavy metals (Pb, Mn, Cr and Cd). We have estimated the concentration of these heavy metal at different points of river Ganga as well as at confluence point of Ganga and Varuna rivers as follows: Pb 1.29 mg/L, Mn 1.325 mg/L, Cr 0.169 mg/L and Cd 0.161mg/L, which was above than the permissible limits stated by Environment protection agency EPA in drinking water. Randomly seven indigenous species of fishes were collected from the wild and were processed for checking the occurrence of these metals in the tissues such as Gills, Liver and Muscle. In all the seven selected fish species, degree of heavy metal concentration followed liver > gills > muscles. Highest accumulation of Pb was observed in Cyprinus carpio liver (8.86 µg/g) and lowest in Baikari muscles (0.07 µg/g). Total THQ value i.e. hazard index (HI) of metals was calculated for these fish species that are frequently consumed and the data showed HI values in following sequence: C.carpio > O. nilotus > C.punctatus > J.coitor > M.armatus > M.tengara > Baikari . Average HI value for C. carpio and O. nilotus was found above 1 which indicates that intake of heavy metals through these species may cause health hazard for human. Maximum HI was recorded in Carpio , which is highly consumed fish by human, hence may be harmful to them. These findings pose a threat to human population and hence needs regular monitoring of metals in fishes to prevent entry into food chain and its effect on the human beings. Toxicology Animal Science Ganga heavy metals pollution fishes health risk assessment THQ Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Heavy metal pollution is a very aggravating problem affecting both aquatic and terrestrial ecosystems worldwide. Several rivers are known to be affected by this pollution and problems are more with the rivers which are given sacred importance, as they are highly exposed to human interventions. Our very prestigious and holy river Ganga is the largest river of the Indian subcontinent, with spiritual significance in Indian culture and has the highest exposure to several such anthropogenic pollutants. After traveling 2525 km and covering 8,61,404 km 2 of the drainage basin, through Uttarakhand, Uttar Pradesh, Bihar, Jharkhand and West Bengal, it discharges its water into Bay of Bengal. But the river has faced major sequential and spatial challenges in its waters and biodiversity in recent times due to poor sanitation, agricultural runoff, household waste and the rapid pace of anthropogenic activities. Heavy metals are one of the most indestructible pollutants, having a long life span that pollutes and extends to the next trophic levels in the ecosystem (Maurya et al., 2016). Aquatic organisms including fish, zooplankton, benthic algae etc. are frequently exposed to heavy metals and show significant metal accumulation variance. Not only this, but heavy metal pollution adversely affects the self-purification and antimoicrobial properties of Ganga water and its flora and fauna diversity, resulting in changes of physical, chemical & biological properties and affect the river ecosystem (Usmani et al., 2017). Different sites and seasonal studies have reported that carcinogenic metals like As, Cd, Cr, Hg, Ni and Pb, were exceeding the WHO permissible limit for potable Ganga water (Sinha et al., 2007 ; Pandey et al., 2010 ; Katiyar et al., 2011) and concluded that Ganga water is unfit for human consumption even for household works. The River Ganga is home to about 140 species of fishes including exotic varieties (Sarkar et al., 2012 ) and are the ultimate recipients, endangered by natural toxins and one of the leading bio-indicators of these metal pollution (Khanna et al., 2007 ). Gills and oral ingestion contaminated food and sediment particles are the main sources of entry, while the liver, kidneys, gills, muscles, skin and brain are the main organs of their accumulation (Vaseem et al., 2013). As a potential source of protein, essential minerals, vitamins, and unsaturated fatty acids (Medeiros et al., 2012 ) in the human diet, about 20 kg year − 1 per capita fishes are consumed worldwide and 50% of global consumption by Indians, contributes − 8–9 kg per year for fish eaters (FAO, 2022). Numerous hazardous elements bio accumulate and biomagnifies in the fishes of Ganga (Mitra et al., 2012 ; Singh, 2014 ). These metals after going through food chain can also enter the human system and contribute to a serious health risk to a person through environmental and food exposure causing various health problems. Minamata disease in Japan due to mercury poisoning is a worldwide phenomenon. Itai Itai disease due to cadmium poisoning is another well-known example. The WHO in 2010 classified lead (Pb), cadmium (Cd), mercury among the top ten chemicals of major public health concern (WHO, 2010). They affect vital organs such as the kidneys, liver, and brain causing nephrotoxicity, hepatotoxicity, and neurotoxicity. Inside the body, some metals bind to sulfur-containing enzymes and disrupt their function. Some may lead to oxidative stress due to their potential to generate free radicals (Jaishankar et al., 2014 ). Exposure to high cadmium may lead to kidney damage and bone fractures (Jarup, 2003 ; Maurya et al., 2016). Prolonged exposure to arsenic in drinking water is strongly associated with increased risk of skin cancer, as well as other types of cancer, as well as other skin lesions such as hyperkeratosis and pigmentation changes (Jarup, 2003 ). Al complexed with Amyloid β disrupt Ca 2+ homeostasis and inhibits mitochondrial respiration in the neuronal cells by interfering with enzymes of electron transport chain, ultimately leading to neuronal cell death (Drago et al., 2008 ). Metal toxicity depends on the dose absorbed, the route of exposure, and the duration of exposure, whether negative or chronic. Deliberate use of arsenic in the case of attempted suicide or accidental exposure to child may also result in severe toxicity (Mazumder, 2008 ). High doses can lead to death, usually within 2 weeks after the onset of symptoms. The acute lethal dose of arsenic in human is 0.6mg/kg/day (ATSDR, 1989; Ratnaike, 2003 ). Cadmium exposure to humans can cause kidney damage and effects on bone, may easily lead to fracture (Jarup et al., 2009). The current study was conducted in the Varanasi region of Uttar Pradesh, one of the busiest industrialized cities in India. The city discharges its HM-containing contaminants into the river through many wastewater treatment plants. The specific aim of the present study is to examine the load of metals especially lead (Pb), manganese (Mn), chromium (Cr) and cadmium (Cd) in water and tissues such as gills, muscle and liver of different fish species of the Ganga River that are frequently used for human consumption in Varanasi region. Our aim is also to find out the heavy metal load in river Ganga (water and fishes) and the potential health risk for the consumers due to the consumption of heavy metal contaminated fishes. 2. Material And Methods 2.1 Description of study area River Ganga travels 2525 km, covers a basin of 1,086,000 km 2 occupying approximately 26.2% geographical area of India. Its alluvial plain represents densest population of the world. Several industries and cities are situated on its bank. The climate contributes long and hot summer (March-June), monsoon (June-September) and winter seasons (November-February) in Ganga. Present study is done in Varanasi (25° 20’N and 83 ° 00’E) an industrially and spiritually important resident hub of north India. The district is registered with several small and large-scale industries including carpet, textiles, Diesel and locomotive workshops paper, food, medical and rubber-plastic, and glass industries whose effluents are either partially or without treatment discharged into the river. Ten different study sites (Fig. 1 ) were selected based on severe anthropogenic activities like ritual bathing, religious offerings, cremation of dead bodies and the places where city’s heavy discharge of sewage and waste water takes place. Such activities affect heavy metal concentrations in surface, ground water and aquatic habitat. 2.2 Collection of samples 2.2.1. Water Water samples were collected from approximately 50–100 cm from the bank of each collection sites mentioned in Fig. 1 in 1000 ml pre-sterilized bottles from 10 different locations. Sampling was done at the early morning because morning hours are with least human interventions, water flow is stable and its contents are uniformly distributed. The water was collected in plastic bottles and immediately kept in an ice box (4°C) and transported to the laboratory. Table 1 Biometric observations in fish species. S.N. Fish species Inhabit stratum Feeding habit Conservation status No. of samples Weight (gm) Length (cm) Local name Family Scientific name 1 Sauri Channidae Channa gachua Middle and lower Ganga surface Carnivorous Least concern 6 7–12 15–20 2 Baikari Schilbeidae Clupisoma garua demarsal Insects,shrimp,crustaceans Least concern 6 3–5 15–18 3 Bam Congridae Mastacembelus armatus demersal Insect larvae and blackworms Least concern 6 10–15 18–25 4 Tengra Bagridae Mystus tengara demarsal zooplanktons Least concern 7 23–35 20–25 5 Carpio Cyprinidae Cyprinus carpio Benthopelagic detri-omnivore Critically endangered 6 25–32 20–30 6 Pathri Sciaenidae Johnius coitor demersal Cephalopods, crustaceans Least concern 5 8–10 5–8 7 Tilapia Cichlidae Oreochromis niloticus Benthopelagic Benthic algae, insect larvae Least concern 6 22–27 15–20 2.2.2 Fish Local fishermen were contacted for capturing the fishes from the wild on the basis of their availability. Gill net was used for capturing the fishes, during summer season consecutively for 3 years from 2019 to 2021. Seven species of fishes were randomly selected from the wild directly from river Ganga on the basis of their availability. Figure 2 depicts the pictures of collected fishes. The collected samples were bought to the laboratory in a polyethylene bag via ice stored transportation. The sampling sites were those having entry points of sewage water and also with maximum human interventions, namely site 1, site 2, site 3, site 4 and site 10 as mentioned in Fig. 1 . Identification of fishes were done by key identifying features (Srivastava., 2019). On the same day within 2 hours, biometrics study was done followed by dissection and collection of target organs (gills, liver and muscles) and stored at -20°C until further processing. 2.3 Sample preparation 2.3.1 For physicochemical parameters Physicochemical parameters in the water are studied and analyzed on five parameters. pH and TDS (Total Dissolved Solid) was measured on the spot by digital Ph meter and probe method respectively by dipping the instrument into water. For BOD (Biological Oxygen Demand), initial DO was measured by titration method and incubating the sample in 20°C for 5 days in dark followed by final DO measurement. Fecal coliform was measured by Plate count method. For fecal coliform , 0.1–0.2 ml of water is dropped in agar medium in petriplate and incubated in bacteriological incubator in 44.5°C for 24 hours. Bacterial colony is counted and calculated by the formula: \(\frac{\mathbf{n}\mathbf{o}.\mathbf{o}\mathbf{f} \mathbf{c}\mathbf{o}\mathbf{l}\mathbf{o}\mathbf{n}\mathbf{i}\mathbf{e}\mathbf{s} \mathbf{X} 100}{\mathbf{d}\mathbf{i}\mathbf{l}\mathbf{u}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}}\) (Eq. 1) Table 2 Physicochemical parameters of sampled fgtc water. Parameters Drainage site Other river site Bureau of Indian Standard (BIS) Permissible limit TDS (mg/L) 545 ± 28.47 302.58 ± 47.14 2000mg/L pH 7.45 ± 0.41 8.05 ± 0.05 6.5–8.5 DO (mg/L) 3.04 ± 0.84 7.02 ± 0.78 4–6 mg/L BOD (mg/L) 53.77 ± 9.21 4.72 ± 2.04 3.0 mg/l Fecal coliform (/100ml) 23x10 6 -60x10 6 136x10 3 -12 x10 3 Nil/100ml *Drainage sites are site no.1,2,10 as per mentioned in Fig. 1 . *Other river sites are site no.3–9 as per mentioned in Fig. 1 . 2.3.2 For heavy metals detection Water Each 80 ml water sample was filtered to remove unwanted macroscopic substances and digested with aqua regia, HCl: HNO 3 (3:1) following APHA, 2017 method (APHA, 2017). Acid mixed samples were subjected to thermostatically controlled Hot plate digestion up to 60°C for 15 minutes. Allowed to cool, filtered through Whatmann-42 filter paper and analyzed in AAS Fish Dried tissues were digested in conc. HNO 3 and H 2 O 2 at 1:1 ratio in microwave digestion system at 130°C, diluted with Milli Q water and filtered with Whatman filter paper number 42. The samples were further diluted with Milli Q water for analysis. 2.4. Instrument A Perkin Elmer, PinAAcle Atomic Absorption Apectrometer (AAS) with Zeeman background correction system equipped with a flame furnace was used to measure Mn, Pb, Cd and Cr in the samples using an external standard method. Detection limit of the instrument was 0.127 mg/L for Mn, 0.18 mg/L for Pb, 0.052 mg/L for Cd and 0.096 mg/L for Cr. 2.4.1. Quality assurance and quality control (QA/QC): The quality assurance and quality control (QA/QC) Analytical estimation was performed using NIST traceable Certified Reference Material of Multielement standard with purity of more than 99.99%. The Atomic Absorption Spectrometer (AAS), Perkin Elmer, PinAAcle 900F was calibrated with three-point calibration in triplicate. The sample were analyzed in triplicate with a mandatory blank sample for all the estimations during study. The QA/QC data is depicted in Table 3 . Table 3 QA/QC results of analytical methods for heavy metal concentrations. Element Detection Limit, mg/L Recovery, % RSD*, % Mn 0.127 103.8-106.5 1.8 Pb 0.180 93.6-106.7 10.2 Cd 0.052 95.6-108.7 9.5 Cr 0.096 88.4-105.3 13.2 *Relative Standard Deviation 2.5. Experimental analysis Heavy metals concentration in water sample from river Ganga was calculated by the formula given below: \(\mathbf{H}\mathbf{e}\mathbf{a}\mathbf{v}\mathbf{y} \mathbf{m}\mathbf{e}\mathbf{t}\mathbf{a}\mathbf{l} \mathbf{c}\mathbf{o}\mathbf{n}\mathbf{c}\mathbf{e}\mathbf{n}\mathbf{t}\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}=\frac{\mathbf{A}\mathbf{A}\mathbf{S} \mathbf{r}\mathbf{e}\mathbf{a}\mathbf{d}\mathbf{i}\mathbf{n}\mathbf{g}}{\mathbf{V}\mathbf{o}\mathbf{l}\mathbf{u}\mathbf{m}\mathbf{e} \mathbf{o}\mathbf{f} \mathbf{t}\mathbf{h}\mathbf{e} \mathbf{s}\mathbf{a}\mathbf{m}\mathbf{p}\mathbf{l}\mathbf{e}}\) (Eq. 2) In fishes, the concentration of heavy metals in fish tissue was calculated as: \(\mathbf{H}\mathbf{e}\mathbf{a}\mathbf{v}\mathbf{y} \mathbf{m}\mathbf{e}\mathbf{t}\mathbf{a}\mathbf{l} \mathbf{c}\mathbf{o}\mathbf{n}\mathbf{c}\mathbf{e}\mathbf{n}\mathbf{t}\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}=\frac{\mathbf{A}\mathbf{A}\mathbf{S} \mathbf{r}\mathbf{e}\mathbf{a}\mathbf{d}\mathbf{i}\mathbf{n}\mathbf{g}}{\begin{array}{c}weight of the sample \left(\mathbf{g}\mathbf{m}\right)\\ \end{array}}\) (Eq. 3) 2.6. Bioaccumulation factor Bio concentration factor is the ratio of the contaminant in an organism to the concentration in the ambient environment in the steady state, where the organism can take in the contaminant through ingestion with its food as well as through direct contact. BCF was calculated using the formula suggested by (Lau et al., 1998 ). \(\mathbf{B}\mathbf{i}\mathbf{o}\mathbf{a}\mathbf{c}\mathbf{c}\mathbf{u}\mathbf{m}\mathbf{u}\mathbf{l}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n} \mathbf{f}\mathbf{a}\mathbf{c}\mathbf{t}\mathbf{o}\mathbf{r}=\frac{\mathbf{C}\mathbf{o}\mathbf{n}\mathbf{c}\mathbf{e}\mathbf{n}\mathbf{t}\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n} \mathbf{o}\mathbf{f} \mathbf{h}\mathbf{e}\mathbf{a}\mathbf{v}\mathbf{y} \mathbf{m}\mathbf{e}\mathbf{t}\mathbf{a}\mathbf{l}\mathbf{s} \mathbf{i}\mathbf{n} \mathbf{f}\mathbf{i}\mathbf{s}\mathbf{h} \mathbf{t}\mathbf{i}\mathbf{s}\mathbf{s}\mathbf{u}\mathbf{e}}{\mathbf{C}\mathbf{o}\mathbf{n}\mathbf{c}\mathbf{e}\mathbf{n}\mathbf{t}\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n} \mathbf{o}\mathbf{f} \mathbf{h}\mathbf{e}\mathbf{a}\mathbf{v}\mathbf{y} \mathbf{m}\mathbf{e}\mathbf{t}\mathbf{a}\mathbf{l}\mathbf{s} \mathbf{i}\mathbf{n} \mathbf{s}\mathbf{u}\mathbf{r}\mathbf{r}\mathbf{o}\mathbf{u}\mathbf{n}\mathbf{d}\mathbf{i}\mathbf{n}\mathbf{g} \mathbf{w}\mathbf{a}\mathbf{t}\mathbf{e}\mathbf{r}}\) (Eq. 4) 2.7. Estimated daily intake Fish muscles are the major source of food for 50% of the human population. Therefore, fish muscles are used for calculating the human health risk through an estimated daily intake (EDI) of metals. Estimated daily intake (EDI) is calculated by the following equation as per (Song et al., 2009 ). \(\text{E}\text{D}\text{I} (\text{m}\text{g}/\text{k}\text{g} \text{b}\text{o}\text{d}\text{y} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{c}\text{o}\text{n}\text{s}\text{u}\text{m}\text{e}\text{r}/\text{d}\text{a}\text{y}) =\frac{\left(\text{C}\text{o}\text{n}\text{c}\text{e}\text{n}\text{t}\text{r}\text{a}\text{t}\text{i}\text{o}\text{n} \text{o}\text{f} \text{m}\text{e}\text{t}\text{a}\text{l} \text{x} \text{W}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{f}\text{i}\text{s}\text{h} \text{c}\text{o}\text{n}\text{s}\text{u}\text{m}\text{e}\text{d} \text{p}\text{e}\text{r} \text{d}\text{a}\text{y}\right)}{\text{B}\text{o}\text{d}\text{y} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{c}\text{o}\text{n}\text{s}\text{u}\text{m}\text{e}\text{r}}\) (Eq. 5) where, the concentration of metals in muscles was converted into dry weight by dividing with a concentration factor 4.8.as per (Rahman et al., 2012 ). The average weight of fish consumed per day is 25g as suggested by a North India survey study by (Kumar et al., 2020 ), and average body weight of consumer is 52 for Indian men (Jain et al., 1995 ; Dang et al., 1996 ). 2.8. Human health risk assessment Heavy metal accumulation in a food chain is one of the risk factors for human health. Some metals adversely affect the nervous system (Briffa et al., 2020 ) and many are reported to be carcinogenic (Faroon et al., 2012 ). This study will be a pioneer for neurotoxic risk of heavy metals through the consumption of the common fishes. In order to assess the risk due to consumption of metal-loaded fishes, we calculated estimated daily intake (EDI) (Song et al., 2009 ), target hazard quotient (THQ) and hazard index (HI) which gives an account of potential risk on health due to heavy metals consumption through contaminated food (Chary et al., 2008 ; Hough et al., 2004 ) and calculated as \(\mathbf{T}\mathbf{H}\mathbf{Q}=\frac{\mathbf{E}\mathbf{D}\mathbf{I}}{\mathbf{R}\mathbf{f}\mathbf{D}}\) (Eq. 6) Where EDI is calculated as per Eq. 5. RfD is the standard dose intake of a particular metal in a day (mg/kg body weight/day) that is under tolerable and healthy range (USEPA, 2011 ), given in table no 8. A THQ more than 1 indicates deleterious health effect due to contaminated food exposure in the population. HI indicates risk due to multiple metals present in contaminated food and calculated as: \(\mathbf{H}\mathbf{I}=\sum \mathbf{T}\mathbf{H}\mathbf{Q}\) (Eq. 7) (USEPA, 2011 ) 2.9 Statistical analysis: The significant difference between heavy metal contamination at different sampling sites were compared using one way anova. The significant difference between concentration of heavy metals and their bioaccumulation in various fish tissues were compared using Two Way Anova test and correlation test was done by Pearson’s correlation matrix to show the inter elemental relation. 3. Results And Discussion 3.1. Analysis of physicochemical properties of water in Varanasi The physicochemical qualities of river water samples gathered from ten different sites of Varanasi are shown in Table 2 . The temperature of the river water in the studied period ranged from 18 to 30°C with an average temperature of 27°C. This result was stable over time. The pH value observed indicates lower pH towards the drainage site than other river sites, indicating acidic water quality towards the drain, which may be due to more CO 2 . The solubility of metal ions in water also has an impact on pH (Sener et al., 2017 ; Osibanjo et al., 2011 ) where lower pH indicates higher solubility and vice versa. Although higher average pH (9.6) in the Varanasi district was observed indicating alkaline nature due to the presence of weak acid and strong bases like carbonates, bicarbonates, and hydroxides in the water body (Maurya et al., 2019 ). Alkalinity of water increases on pollution load from upstream to downstream, say from Kanpur to Varanasi (Gupta et al., 2013 ). Although Ganga water holds buffering capacity, nevertheless this pH is unsuitable for human consumption as well as for the healthy survival of fishes. However, according to European Union, fisheries and aquatic life 6.0 to 9.0 pH limits is recommended (USEPA, 1986 ; USEPA, 1999a ). Dissolved Oxygen determines the purity of water and life within the water body. The observed DO is below the permissible limit at the drainage site and within range at other river sites, indicating highly impure water at the drainage site due to heavy sewage discharge from the city. Aquatic aerobic bacteria consume oxygen from water for the decomposition of wastes, thus increasing biological oxygen demand (BOD). In the present study, average BOD was measured at 53.77 mg/L at the drainage site (Table.2) showing high organic pollution which may be due to untreated domestic sewage, agriculture runoff, and residual fertilizers. 3.2 Heavy metal analysis in water The heavy metals concentrations in the ten selected sites are recorded and presented in Table 4 . Concentration of Pb, Mn, Cd and Cr were recorded highest at Varuna Ganga confluence point followed by Nagwa and Raj ghat. These points are noted to have highest sewage discharge from the city and are considered among drainage sites. The highest Lead (Pb) concentration was recorded 1.297 mg/L which was much above than the permissible limits stated by Environment protection agency (EPA). (Table 4 ) Similarly, Mn, Cr and Cd were also reported above the permissible range. Similar study was conducted at Kanpur, Allahabad, Mirzapur and Varanasi districts of Uttar Pradesh and observed that river Ganga water loaded with Pb 0.24 mg/l, Cd 0.85 mg/l and Cr 0.45 mg/l concentrations in Varanasi in 2019 (Maurya et al., 2019 ). These metal contamination were statistically significant at different sampling sites with p < 0.5. The interaction of heavy metals with water, sediment and aquatic lives is responsible for their transport in the environment (Sarkar et al., 2016 ). The results of the present study indicated that, industrial effluent discharge and agricultural runoff, released into the Ganga River in Varanasi is polluted with heavy metals and unfit for human consumption. Accumulation of these persistent pollutants may cause huge risk for the fish and human consuming edible fishes. Table 4 Showing heavy metal contamination in mg/L at different sampling sites. Statistical significance of heavy metal contamination at different sampling sites was done using One Way Anova and the differences were significant at p < 0.5, f = 1.6309 Sites Pb Mn Cr Cd Permissible limit as per EPA * 0.05 mg/L 0.05 mg/L 0.1 mg/L 0.005 mg/L Nagwa 1.093 ± 0.054 0.221 ± 0.011 0.164 ± 0.008 0.156 ± 0.007 Samne ghat 0.477 ± 0.023 0.200 ± 0.010 0.146 ± 0.007 0.131 ± 0.006 Assi ghat 0.140 ± 0.007 0.141 ± 0.007 0.144 ± 0.007 0.130 ± 0.006 Tulsi ghat 0.017 ± 0.00 0.128 ± 0.006 0.140 ± 0.007 0.124 ± 0.006 Harishchandra ghat 0.158 ± 0.007 0.153 ± 0.007 0.157 ± 0.007 0.155 ± 0.007 Shivala 0.075 ± 0.003 0.143 ± 0.007 0.143 ± 0.007 0.123 ± 0.006 Dassaswamedh ghat 0.146 ± 0.007 0.193 ± 0.009 0.147 ± 0.007 0.140 ± 0.007 Manikarnika ghat 0.181 ± 0.009 0.175 ± 0.008 0.156 ± 0.007 0.152 ± 0.007 Raj ghat 0.281 ± 0.014 0.181 ± 0.009 0.153 ± 0.007 0.153 ± 0.007 Varuna ganga confluence 1.297 ± 0.064 1.325 ± 0.06 0.169 ± 0.008 0.161 ± 0.008 * EPA: Environment Protection Agency ( FEPA, 2003). 3.3. Analysis of heavy metals in fish tissues. The collected fish tissue samples of gills, liver and muscles were estimated for the accumulation of heavy metals (Table 5 ). In all the seven fish species, the degree of heavy metal concentration followed liver > gills > muscles. Liver being an important organ for detoxification as well as for protein synthesis may be a possible reason for having the highest metal affinity (Fernandes et al., 2008 ). Gills have a large surface area, and are in continuous contact with the aquatic environment, therefore are the second most important site for metal concentration. Another reason may be due to the increased number of chloride cells that pick up metal ions from contaminated water (Mazon et al., 1999 ; Costa et al., 2002). Although fish muscles are consumed as protein source all over the globe, it is a metabolically less active tissue (Adhikari et al., 2009 ; Radhakrishnan, 2010 ) and the reason for least accumulation of metals in muscles. Less extensive blood circulation in muscles in comparison to other vital organs like liver, kidney and gills is also a major factor. The heavy metal trend was Mn > Cr > Pb > Cd in almost all the species and tissues. Probable reason for more Mn concentration could be cumulative role of water contamination and essential elemental nature of Mn in enzymatic activity (Altaf et al., 2016 ). Cr enters the aquatic system via multiple industrial sources (Ghosh, 2002 ; Bagchi et al., 2001 ) from where Hexavalent form of chromium is reported to diffuses readily in the fish tissue and penetrates cell membrane (Ahmed et al., 2013 ). Few previous results show Cd and Pb were more than Cr in fish tissue (Maurya et al., 2019 ; Ghosh, 2002 ; Javed et al., 2013; Begum et al., 2013 ). In the present study, the highest concentration Pb was observed in Carpio liver (8.86 µg/g) and lowest in Baikari muscles (0.07 µg/g). The FAO proposed a limit of 0.5 µg/g for Pb in food (FAO, 1983 ) while FEPA (Food and Environment Protection Act) set this value to 2.0 µg/g (FEPA, 2003). Mn was recorded highest in Pathari liver (53.19 µg/g) and lowest in Baikari muscles (1.10 µg/g). Cr was estimated highest in Pathari liver whereas lowest in Bam muscles. European Union Commission (EUC) suggested the daily tolerable chromium concentration to be 1 µg/g, while the FEPA suggested 0.15 µg/g and WHO suggested 0.15 µg/g (FEPA, 2003). Cadmium (Cd) is a severe pollutant and an extremely noxious element, transported in water. Different industrial and domestic channels induced in the Ganga River may be the source of Cd contamination. Table 5 Concentration of heavy metals in different fish tissue (µg/g) and their permissible range by FAO. Statistical significance of heavy metal concentration in various fish tissues was done using two way Anova test and the differences were significant at p < 0.05, F tissue = 10.144, F metals 14.339 and F tissue X Metals = 2.312. Species Tissue Pb Mn Cr Cd Permissible Limit as per FAO * 0.2 µg/g 0.98 µg/g 0.05 µg/g 0.02 µg/g Sauri Gills 2.905 ± 0.14 17.829 ± 0.891 2.046 ± 0.102 0.427 ± 0.021 Liver 3.248 ± 0.16 19.858 ± 0.992 3.978 ± 0.198 0.452 ± 0.022 Muscles 2.778 ± 0.13 12.419 ± 0.620 2.896 ± 0.144 0.275 ± 0.013 Baikari Gills 1.284 ± 0.06 4.129 ± 0.206 3.165 ± 0.158 0.075 ± 0.003 Liver 1.449 ± 0.07 4.328 ± 0.216 3.706 ± 0.185 0.120 ± 0.006 Muscles 0.079 ± 0.003 1.106 ± 0.055 3.145 ± 0.157 0.025 ± 0.001 Carpio Gills 4.146 ± 0.20 8.842 ± 0.442 5.115 ± 0.255 1.906 ± 0.095 Liver 8.868 ± 0.44 15.614 ± 0.780 25.704 ± 1.285 3.274 ± 0.163 Muscles 2.316 ± 0.11 3.157 ± 0.157 4.993 ± 0.249 2.487 ± 0.124 Tilapia Gills 3.876 ± 0.19 6.872 ± 0.343 9.094 ± 0.454 0.143 ± 0.007 Liver 5.025 ± 0.25 8.432 ± 0.421 9.845 ± 0.492 0.158 ± 0.007 Muscles 0.784 ± 0.04 1.7380 ± 0.086 2.363 ± 0.118 0.129 ± 0.006 Tengra Gills 6.435 ± 0.32 13.344 ± 0.667 1.689 ± 0.084 0.681 ± 0.034 Liver 7.920 ± 0.39 19.166 ± 0.958 2.371 ± 0.118 ND Muscles 0.614 ± 0.03 1.766 ± 0.088 1.281 ± 0.064 ND Bam Gills 5.342 ± 0.267 17.884 ± 0.894 4.656 ± 0.232 ND Liver 7.651 ± 0.382 24.076 ± 1.203 5.467 ± 0.273 ND Muscles 1.684 ± 0.084 3.513 ± 0.175 0.489 ± 0.024 ND Pathari Gills 5.904 ± 0.295 25.425 ± 1.271 2.577 ± 0.128 ND Liver 7.354 ± 0.367 53.193 ± 2.659 29.467 ± 1.473 ND Muscles 1.886 ± 0.094 6.288 ± 0.314 0.701 ± 0.035 ND *FAO: Food and Agriculture Organisation ( FAO, 2022). Highest Cd was recorded in Carpio liver (3.27 µg/g) and remains undetected in tengra, bam and pathari. Carpio is larger in size, so its higher biomass can be considered for higher accumulation of metals. However small size of pathari fish gains importance because smaller body size reduces the metal accumulation through surface action. Our study observed 0.158 µg/g Cd in Tilapia liver. The concentration level of each metal in fish tissue was statistically significant at p < 0.05. In similar Egyptian studies in Lake Nasser, the liver of O. niloticus was reported with 1.38 mg/kg dry weigh Cd whereas it remained undetected in fish tissues from Wadi Al-Rayan Lake (Sally et al., 2020; Dalia et al., 2021 ). Whereas the lesser accumulation in Tengra was observed in previous study (Maurya et al., 2019 ). Variation of heavy metal concentration in fish tissues may be due to metal contamination in the surrounding water in which fish travels. Age is also another important factor because time they spend in water decide the concentration of metals in their body since fishes were captured at their different life period. Similar study was done where Cd was accumulated highest in liver tissue of bottom feeder followed by column and surface feeder fishes (Kumar et al., 2020 ). Different concentration of heavy metals in different fish species might be the result of different ecological needs, metabolism and feeding habit. 3.4 . Correlation analysis of heavy metal in fish tissue Inter elemental relation is shown by Pearson's correlation matrix (Table 6 ). The correlation coefficient ranges between − 1 to + 1. A positive correlation between two variable means for every positive increase in one variable, there is a positive increase of a fixed proportion in the other,while a negative correlation indicates that for every positive increase in one variable, there is a negative decrease of a fixed proportion in the other. In our study, we found notable correlation between Pb and Cd (r = 0.72, p < 0.05). Table 6 Shows inter elemental relation through Pearson's correlation matrix. Heavy metals Pb Mn Cr Cd Pb 1 Mn 0.1975 1 Cr 0.2727 0.2952 1 Cd 0.7205 -0.2414 0.3649 1 The probable reason is due to the high concentration of these two elements in Carpio and Tengra in the all the selected fish organs. Cd and Pb was reported to occur in leaded petrol, coal cumbustion, smelting and old pre industrial lead. Accumulation of Cd and Pb by C. catla and C. mrigala had already been observed in other studies (Dhanakumar et al., 2015 ). The negative correlation was calculated in case of Cd and Mn, while in case of Pb to Mn, Pd to Cr, Mn to Cr, and Cr to Cd, there were non-significant positive correlations (p < 0.05) 3.5. Determination of bio-accumulation factor For studying ecological risk assessment, Bio accumulation factor (BAF) is studied to know the concentration of heavy metals transferred from water dwelling organism from the surrounding water. As shown in Table 7 , BAF in each fish species followed the same trend in organs liver > gills > muscles and all metals had tissue concentrations higher than their corresponding concentrations in water. Bioaccumulation of heavy metals in fish tissues, as well as between four metals were statistically significant at p < 0.05 .This report was supported by other studies in different fish species and different water bodies where accumulation of HM in fishes showed a site dependent response (Maurya et al., 2018; Elhaddad et al., 2022 ; Olaifa et al., 2004 ). Figure 3 shows bio concentration factor of all the four metals in each fish. This is because metabolically active tissues show higher BAF than other less active tissues like muscles (Chale, 2002 ). Table 7 Bio-accumulation factor in different fish tissues. Statistical significance of heavy metal accumulation in various fish tissues was done using two way Anova test and the differences were significant at p < 0.05, F tissue = 9.052, F metals = 10.82 and F tissue X Metals = 2.2664. Species Tissue Pb Mn Cr Cd Sauri Gills 7.506 ± 0.37 63.676 ± 3.18 13.417 ± 0.67 2.985 ± 0.14 Liver 8.392 ± 0.42 70.924 ± 3.54 26.083 ± 1.30 3.160 ± 0.15 Muscles 7.178 ± 0.35 44.356 ± 2.21 18.987 ± 0.94 1.928 ± 0.09 Baikari Gills 3.318 ± 0.16 14.749 ± 0.73 20.752 ± 1.03 0.530 ± 0.02 Liver 3.744 ± 0.18 15.458 ± 0.77 24.295 ± 1.21 0.842 ± 0.04 Muscles 0.205 ± 0.01 3.950 ± 0.19 20.620 ± 1.03 0.178 ± 0.00 Carpio Gills 10.714 ± 0.53 31.578 ± 1.57 33.535 ± 1.67 13.324 ± 0.66 Liver 22.914 ± 1.14 55.765 ± 2.78 168.506 ± 8.42 22.887 ± 1.14 Muscles 5.985 ± 0.29 11.276 ± 0.56 32.735 ± 1.63 17.391 ± 0.86 Tilapia Gills 10.015 ± 0.50 24.543 ± 1.22 59.620 ± 2.98 0.999 ± 0.05 Liver 12.984 ± 0.64 30.116 ± 1.50 64.545 ± 3.22 1.107 ± 0.05 Muscles 2.026 ± 0.10 6.207 ± 0.31 15.491 ± 0.77 0.905 ± 0.04 Tengra Gills 16.626 ± 0.83 47.657 ± 2.38 11.076 ± 0.55 4.764 ± 0.23 Liver 20.464 ± 1.02 68.451 ± 3.42 15.544± 0 Muscles 1.587 ± 0.08 6.308 ± 0.31 8.401 ± 0.42 0 Bam Gills 13.803 ± 0.69 63.874 ± 3.19 30.523 ± 1.52 0 Liver 19.7683 ± 0.98 85.988 ± 4.29 35.841 ± 1.79 0 Muscles 4.352 ± 0.21 12.548 ± 0.62 3.209 ± 0.16 0 Pathari Gills 15.254 ± 0.76 90.805 ± 4.54 16.897 ± 0.84 0 Liver 19 ± 0.95 189.97 ± 9.49 193.176 ± 9.65 0 Muscles 4.873 ± 0.24 22.457 ± 1.12 4.594 ± 0.23 0 3.6 . Health risk assessment. The water quality of river Ganga is degraded due to heavy metals contamination as shown by our study and this can impact human health by direct consumption or contaminated fishes captured from river Ganga. The Estimated Daily Intake of different metals via all the collected fishes are shown in Fig. 4 . The EDI for Pb was measured higher than the recommended daily allowance in Sauri, Carpio, Bam and Pathari. Mn was higher in Sauri and Baikari. EDI for Cr was higher than the recommended daily allowance in all the species. While Cd was higher in Sauri, Tilapia and Carpio.. Table 8 Showing Estimated daily intake (EDI), Recommended dose (RfD) established by USEPA (USEPA. 1999a) Target Hazard Quotient (THQ), Hazard index (HI). Fish species Heavy metals Recommended daily allowance mg day- 1 kg − 1 body weight RfD mg kg − 1 day − 1 EDI mg kg − 1 day − 1 THQ HI Sauri Pb Mn Cr Cd 0.25 2.5-3 0.23 0.07 0.004 0.140 1.500 0.001 0.719 4.444 1.902 0.193 0.179 0.031 0.012 0.193 0.417 Baikari Pb Mn Cr Cd 0.25 2.5-3 0.23 0.07 0.004 0.140 1.50 0.001 0.020 0.395 2.066 0.017 0.005 0.002 0.013 0.017 0.039 Carpio Pb Mn Cr Cd 0.25 2.5-3 0.23 0.07 0.004 0.140 1.500 0.001 0.599 1.129 3.280 1.742 0.149 0.008 0.021 1.742 1.922 Tilapia Pb Mn Cr Cd 0.25 2.5-3 0.23 0.07 0.004 0.14 1.500 0.001 0.203 0.622 1.552 0.090 0.050 0.004 0.010 0.091 1.560 Tengra Pb Mn Cr Cd 0.25 2.5-3 0.23 0.07 0.004 0.140 1.500 0.001 0.159 0.632 0.841 0.000 0.039 0.004 0.005 0.000 0.049 Bam Pb Mn Cr Cd 0.25 2.5-3 0.23 0.07 0.004 0.14 1.5 0.001 0.436 1.257 0.321 0.000 0.109 0.008 0.002 0.000 0.120 Pathari Pb Mn Cr Cd 0.25 2.5-3 0.23 0.07 0.004 0.140 1.500 0.001 0.488 2.250 0.460 0.000 0.122 0.016 0.003 0.000 0.141 The Target Hazard quotient (THQ) estimated for individual heavy metals through consumption of different fish species are presented in Table 8 . The acceptance value for THQ is 1, therefore except Cd in Carpio, every metal was below the hazard quotient. Similar result was obtained by other studies where the muscles of fishes were within the permissible limits for human consumption, and target hazard quotient less than 1, may be an indication for less polluted water bodies (Maurya et al., 2019 ); Ahmed et al., 2022 ); Ali et al., 2019 ). Total THQ value i.e. hazard index (HI) of metals was recorded in following sequence: Carpio > Telapia > Sauri > Pathari > Bam > Tengra > Baikari. Average HI value for Carpio and Telapia was found above 1 which indicates that consumption of these contaminated fishes may lead to health hazard for human. Maximum HI was recorded in Carpio, which is among highly consumable fish by human. This demonstrates that Carpio consumption can pose health risk to human. Therefore, regular monitoring of heavy metals in fishes should be performed to prevent excessive concentration in the humans through food chain. 4. Conclusion The outcome of present study reveals that Pb, Mn, Cr and Cd were higher than the permissible limit of international standards (BIS and WHO) (BIS, 1993; WHO, 2017) for drinking water, in river Ganga in Varanasi district, which clearly indicates that Ganga water in this place is not suitable for direct human consumption. Proper water treatment plants are required. Varuna Ganga confluence point and Samne ghat were the most polluted sites, due to which toxic metals like lead and cadmium get accumulated in aquatic lives like fishes. The accumulation is maximum in fish’s liver tissues followed by gills and muscles. Consumption of fishes contaminated with heavy metals could cause health hazard to human. Carpio rated at highest risk for human consumption. Heavy metals contamination in the fish is an alert for the responsible beings to take corrective measures for Ganga River and protect the well-being of aquatic lives and local inhabitants significantly. Abbreviations AAS Atomic absorption spectrophotometer BAF Bioaccumulation factor EDI Estimated daily intake THQ Target hazard quotient HI Hazard Index Pb Lead Mn Manganese Cr Chromium Cd Cadmium Declarations All authors have read, understood, and have complied as applicable with the statement on "Ethical responsibilities of Authors" as found in the Instructions for Authors and are aware that with minor exceptions, no changes can be made to authorship once the paper is submitted. Acknowledgements The authors would like to thank CSIR-Indian Institute of Toxicology Research, Lucknow and Department of Chemical Engineering, IIT, BHU for providing the facilities required to perform this study. Author Contribution Vijay Nath Mishra is behind the idea of this study. Bhargawi Mishra has performed the material preparation, data collection and wrote the first draft of manuscript. Nasreen Ghazi Ansari has performed the experimental part. Geeta J. Gautam helped in data analysis, interpretation and finalizing the manuscript. Rajnish Chaturvedi commented on previous version of the manuscript. All authors read and approved the final manuscript. Funding: There is no funding agency for this study. Ethical declaration : This study involved collection of fishes from wild and direct processing for the estimation of heavy metals in different tissues. The study protocol was assessed and approved by the BHU ethics committee (542/GO/ReBi/S/02/CPCSEA dated 26.05.2017) Data Availability The generated and analyzed datasets during the study are available per request from the corresponding author. Declarations competing interests: The authors declare no competing interests. Ethics Approval and Consent to Participate Not applicable. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2168987","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":144495489,"identity":"88f2c07a-4c7a-49ba-bb41-c70509ba1b17","order_by":0,"name":"Bhargawi Mishra","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYBACAwkIzcPYAKZtgJix8QAJWhLSQFoaiNICBQmHwRReLebSzc8+fqk5LMPcfsbwc+GP83Zr2w8DbamxicalxXLOMePZMscO8zD25BhLz0i4nbztTCJQy7G03AZcDruRYMwswXYb6JccA2keoBazA0AtjA2H8WhJ/8ws8Q+opf+N8W+ehHPJZucfEtKSY8z4sQ2oZUaOGdCWA3ZmNwjYYjkjp5iZse8/UMuzMmuetOQEsxtAWxLw+MVcIn0z449vafaG/cmbb/PY2NmbnU9/+OBDjQ1OLSDAzAMkDBs4DECcRLDKBDzKQYDxB5CQZ2B/AOLYE1A8CkbBKBgFIxAAAICdZFyE0m+HAAAAAElFTkSuQmCC","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Bhargawi","middleName":"","lastName":"Mishra","suffix":""},{"id":144496480,"identity":"a1960a24-2ec4-4cfc-a8d2-fcf726640af9","order_by":1,"name":"Geeta J. Gautam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYNCCiv888uwNQIaBBVHqGRsYzjDLGPYcAGmRIFILYxuzDcONBBCHCC3y7s3HH/xgY+NhnPn86oYfBRIM/O3dCXi1GJ45ltjYw8PDwy6dU3azB+gwiTNnN+DXMiPHsIFHQoKHcXZO2g0eoBYDiVwCWua//9j4x8CAh+HmmbSbf4jRIg80v5knIYGH4Qb7sdtE2WLAk2Y4W+bAAR7Dnhy22zIGEjwE/SLffvjBx7f/DtjLsx9/dvPNHxs5/vZeArYcgDN5DMAkXuVgWxrgTPYHBFWPglEwCkbByAQAcfRIJ/3tv28AAAAASUVORK5CYII=","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Geeta","middleName":"J.","lastName":"Gautam","suffix":""},{"id":144496481,"identity":"2e1972ed-35a7-46e7-827f-bfec84b557cf","order_by":2,"name":"V. N. Mishra","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYJCCA4wNQJK9seFAQgUDgwHxWngOH3zw4QyRWhjAWiTSkg1nthGhxeB2d+LBnzvuyTMw5JhJ8847LG/O3nyA4UfFNtxa7pzdcJj3TLFhA8MZoJZthw139hxLYOw5cxunFskZuRsOM7YlMDYw9oC1MG64kWPAzNiGX8vBn20J9g3MPEAtcw7bE9TCL5G74QBvW0JiAxsb0PsNhxOJ0nIYqCW5gYcZGMjH0pM3nDmWcBCfX9gkcjd/BDrMtkH+ITAqa6xtNxxvPvjgRwVuLXBgfwBMNYPJA4TVI0AdKYpHwSgYBaNghAAAIuZiMj1PQRMAAAAASUVORK5CYII=","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"V.","middleName":"N.","lastName":"Mishra","suffix":""}],"badges":[],"createdAt":"2022-10-15 10:31:10","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-2168987/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2168987/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":27888476,"identity":"090afb8a-46e3-4c75-bf44-afd48d1b1f04","added_by":"auto","created_at":"2022-10-17 19:31:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":142301,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eShowing route of river Ganga in India and 1-10, sampling stations of river Ganga in Varanasi district.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2168987/v1/4f1a73d5cac69d5dbfd362d9.jpg"},{"id":27888477,"identity":"2bdd4501-a766-4745-b7ea-e58072ea7ab9","added_by":"auto","created_at":"2022-10-17 19:31:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":114895,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eShowing pictures of different fish genus captured from river Ganga for the present study. Their detailed scientific description is given in Table 1\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2168987/v1/e951bf27cacc53701b9a1b5b.jpg"},{"id":27888478,"identity":"16d9a738-5dd6-4f1b-8d2a-278066482f81","added_by":"auto","created_at":"2022-10-17 19:31:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":100609,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBio-accumulation factor in different fish species. A:Sauri; B: Baikari; C:Tilapia; D:Carpio E: Baam; F: Tengara; G:Pathari\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2168987/v1/030ca872f4cdff17228cf149.jpg"},{"id":27888479,"identity":"c3b892f1-4e73-4a25-8e32-bb9b249c61ff","added_by":"auto","created_at":"2022-10-17 19:31:42","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":73070,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstimated daily intake of metals via different fish species.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2168987/v1/0809c0332efaa81729ee5eb6.jpg"},{"id":27888481,"identity":"247f41ea-b2f0-4e3c-8d31-bbf43b497033","added_by":"auto","created_at":"2022-10-17 19:31:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1118555,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2168987/v1/3c43243e-5e36-4d80-aef8-3c5c8cf5dfe7.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003e\u003cstrong\u003eBioaccumulation of heavy metals in different fishes of Gangetic river system in Varanasi and its health risk assessment\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHeavy metal pollution is a very aggravating problem affecting both aquatic and terrestrial ecosystems worldwide. Several rivers are known to be affected by this pollution and problems are more with the rivers which are given sacred importance, as they are highly exposed to human interventions. Our very prestigious and holy river Ganga is the largest river of the Indian subcontinent, with spiritual significance in Indian culture and has the highest exposure to several such anthropogenic pollutants. After traveling 2525 km and covering 8,61,404 km\u003csup\u003e2\u003c/sup\u003e of the drainage basin, through Uttarakhand, Uttar Pradesh, Bihar, Jharkhand and West Bengal, it discharges its water into Bay of Bengal. But the river has faced major sequential and spatial challenges in its waters and biodiversity in recent times due to poor sanitation, agricultural runoff, household waste and the rapid pace of anthropogenic activities. Heavy metals are one of the most indestructible pollutants, having a long life span that pollutes and extends to the next trophic levels in the ecosystem (Maurya et al., 2016). Aquatic organisms including fish, zooplankton, benthic algae etc. are frequently exposed to heavy metals and show significant metal accumulation variance. Not only this, but heavy metal pollution adversely affects the self-purification and antimoicrobial properties of Ganga water and its flora and fauna diversity, resulting in changes of physical, chemical \u0026amp; biological properties and affect the river ecosystem (Usmani et al., 2017). Different sites and seasonal studies have reported that carcinogenic metals like As, Cd, Cr, Hg, Ni and Pb, were exceeding the WHO permissible limit for potable Ganga water (Sinha et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Pandey et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Katiyar et al., 2011) and concluded that Ganga water is unfit for human consumption even for household works.\u003c/p\u003e \u003cp\u003eThe River Ganga is home to about 140 species of fishes including exotic varieties (Sarkar et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and are the ultimate recipients, endangered by natural toxins and one of the leading bio-indicators of these metal pollution (Khanna et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Gills and oral ingestion contaminated food and sediment particles are the main sources of entry, while the liver, kidneys, gills, muscles, skin and brain are the main organs of their accumulation (Vaseem et al., 2013). As a potential source of protein, essential minerals, vitamins, and unsaturated fatty acids (Medeiros et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) in the human diet, about 20 kg year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e per capita fishes are consumed worldwide and 50% of global consumption by Indians, contributes \u0026minus;\u0026thinsp;8\u0026ndash;9 kg per year for fish eaters (FAO, 2022). Numerous hazardous elements bio accumulate and biomagnifies in the fishes of Ganga (Mitra et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Singh, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These metals after going through food chain can also enter the human system and contribute to a serious health risk to a person through environmental and food exposure causing various health problems. Minamata disease in Japan due to mercury poisoning is a worldwide phenomenon. Itai Itai disease due to cadmium poisoning is another well-known example.\u003c/p\u003e \u003cp\u003eThe WHO in 2010 classified lead (Pb), cadmium (Cd), mercury among the top ten chemicals of major public health concern (WHO, 2010). They affect vital organs such as the kidneys, liver, and brain causing nephrotoxicity, hepatotoxicity, and neurotoxicity. Inside the body, some metals bind to sulfur-containing enzymes and disrupt their function. Some may lead to oxidative stress due to their potential to generate free radicals (Jaishankar et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Exposure to high cadmium may lead to kidney damage and bone fractures (Jarup, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Maurya et al., 2016). Prolonged exposure to arsenic in drinking water is strongly associated with increased risk of skin cancer, as well as other types of cancer, as well as other skin lesions such as hyperkeratosis and pigmentation changes (Jarup, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Al complexed with Amyloid \u003cem\u003eβ\u003c/em\u003e disrupt Ca\u003csup\u003e2+\u003c/sup\u003e homeostasis and inhibits mitochondrial respiration in the neuronal cells by interfering with enzymes of electron transport chain, ultimately leading to neuronal cell death (Drago et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Metal toxicity depends on the dose absorbed, the route of exposure, and the duration of exposure, whether negative or chronic. Deliberate use of arsenic in the case of attempted suicide or accidental exposure to child may also result in severe toxicity (Mazumder, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). High doses can lead to death, usually within 2 weeks after the onset of symptoms. The acute lethal dose of arsenic in human is 0.6mg/kg/day (ATSDR, 1989; Ratnaike, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Cadmium exposure to humans can cause kidney damage and effects on bone, may easily lead to fracture (Jarup et al., 2009).\u003c/p\u003e \u003cp\u003eThe current study was conducted in the Varanasi region of Uttar Pradesh, one of the busiest industrialized cities in India. The city discharges its HM-containing contaminants into the river through many wastewater treatment plants. The specific aim of the present study is to examine the load of metals especially lead (Pb), manganese (Mn), chromium (Cr) and cadmium (Cd) in water and tissues such as gills, muscle and liver of different fish species of the Ganga River that are frequently used for human consumption in Varanasi region. Our aim is also to find out the heavy metal load in river Ganga (water and fishes) and the potential health risk for the consumers due to the consumption of heavy metal contaminated fishes.\u003c/p\u003e"},{"header":"2. Material And Methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Description of study area\u003c/h2\u003e \u003cp\u003eRiver Ganga travels 2525 km, covers a basin of 1,086,000 km\u003csup\u003e2\u003c/sup\u003e occupying approximately 26.2% geographical area of India. Its alluvial plain represents densest population of the world. Several industries and cities are situated on its bank. The climate contributes long and hot summer (March-June), monsoon (June-September) and winter seasons (November-February) in Ganga. Present study is done in Varanasi (25\u0026deg; 20\u0026rsquo;N and 83\u003csup\u003e\u0026deg;\u003c/sup\u003e00\u0026rsquo;E) an industrially and spiritually important resident hub of north India.\u003c/p\u003e \u003cp\u003eThe district is registered with several small and large-scale industries including carpet, textiles, Diesel and locomotive workshops paper, food, medical and rubber-plastic, and glass industries whose effluents are either partially or without treatment discharged into the river. Ten different study sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were selected based on severe anthropogenic activities like ritual bathing, religious offerings, cremation of dead bodies and the places where city\u0026rsquo;s heavy discharge of sewage and waste water takes place. Such activities affect heavy metal concentrations in surface, ground water and aquatic habitat.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Collection of samples\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Water\u003c/h2\u003e \u003cp\u003eWater samples were collected from approximately 50\u0026ndash;100 cm from the bank of each collection sites mentioned in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e in 1000 ml pre-sterilized bottles from 10 different locations. Sampling was done at the early morning because morning hours are with least human interventions, water flow is stable and its contents are uniformly distributed. The water was collected in plastic bottles and immediately kept in an ice box (4\u0026deg;C) and transported to the laboratory.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBiometric observations in fish species.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.N.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFish species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInhabit stratum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFeeding habit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eConservation status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo. of samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeight (gm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLength (cm)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLocal name\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFamily\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eScientific name\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSauri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChannidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eChanna gachua\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMiddle and lower Ganga surface\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCarnivorous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeast concern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaikari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSchilbeidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eClupisoma garua\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edemarsal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInsects,shrimp,crustaceans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeast concern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15\u0026ndash;18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongridae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eMastacembelus armatus\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edemersal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInsect larvae and blackworms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeast concern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e18\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTengra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBagridae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eMystus\u003c/span\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003etengara\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edemarsal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ezooplanktons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeast concern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarpio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCyprinidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eCyprinus carpio\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBenthopelagic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003edetri-omnivore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCritically endangered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25\u0026ndash;32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePathri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSciaenidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eJohnius\u003c/span\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ecoitor\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edemersal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCephalopods, crustaceans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeast concern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTilapia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCichlidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eOreochromis\u003c/span\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eniloticus\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBenthopelagic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBenthic algae, insect larvae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeast concern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Fish\u003c/h2\u003e \u003cp\u003eLocal fishermen were contacted for capturing the fishes from the wild on the basis of their availability. Gill net was used for capturing the fishes, during summer season consecutively for 3 years from 2019 to 2021. Seven species of fishes were randomly selected from the wild directly from river Ganga on the basis of their availability. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e depicts the pictures of collected fishes. The collected samples were bought to the laboratory in a polyethylene bag via ice stored transportation. The sampling sites were those having entry points of sewage water and also with maximum human interventions, namely site 1, site 2, site 3, site 4 and site 10 as mentioned in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Identification of fishes were done by key identifying features (Srivastava., 2019). On the same day within 2 hours, biometrics study was done followed by dissection and collection of target organs (gills, liver and muscles) and stored at -20\u0026deg;C until further processing.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Sample preparation\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 For physicochemical parameters\u003c/h2\u003e \u003cp\u003ePhysicochemical parameters in the water are studied and analyzed on five parameters.\u003c/p\u003e \u003cp\u003epH and TDS (Total Dissolved Solid) was measured on the spot by digital Ph meter and probe method respectively by dipping the instrument into water. For BOD (Biological Oxygen Demand), initial DO was measured by titration method and incubating the sample in 20\u0026deg;C for 5 days in dark followed by final DO measurement. Fecal coliform was measured by Plate count method.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFor fecal coliform\u003c/b\u003e, 0.1\u0026ndash;0.2 ml of water is dropped in agar medium in petriplate and incubated in bacteriological incubator in 44.5\u0026deg;C for 24 hours. Bacterial colony is counted and calculated by the formula:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\frac{\\mathbf{n}\\mathbf{o}.\\mathbf{o}\\mathbf{f} \\mathbf{c}\\mathbf{o}\\mathbf{l}\\mathbf{o}\\mathbf{n}\\mathbf{i}\\mathbf{e}\\mathbf{s} \\mathbf{X} 100}{\\mathbf{d}\\mathbf{i}\\mathbf{l}\\mathbf{u}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n}}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(Eq.\u0026nbsp;1)\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysicochemical parameters of sampled fgtc water.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrainage site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther river site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBureau of Indian Standard (BIS)\u003c/p\u003e \u003cp\u003ePermissible limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTDS (mg/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e545\u0026thinsp;\u0026plusmn;\u0026thinsp;28.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302.58\u0026thinsp;\u0026plusmn;\u0026thinsp;47.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2000mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5\u0026ndash;8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDO (mg/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u0026ndash;6 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBOD (mg/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.77\u0026thinsp;\u0026plusmn;\u0026thinsp;9.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.72\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 mg/l\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFecal coliform (/100ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23x10\u003csup\u003e6\u003c/sup\u003e-60x10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136x10\u003csup\u003e3\u003c/sup\u003e-12 x10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNil/100ml\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e*Drainage sites are site no.1,2,10 as per mentioned in\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e\u003cb\u003e*Other river sites are site no.3\u0026ndash;9 as per mentioned in\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 For heavy metals detection\u003c/h2\u003e \u003cp\u003e \u003cb\u003eWater\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEach 80 ml water sample was filtered to remove unwanted macroscopic substances and digested with aqua regia, HCl: HNO\u003csub\u003e3\u003c/sub\u003e (3:1) following APHA, 2017 method (APHA, 2017). Acid mixed samples were subjected to thermostatically controlled Hot plate digestion up to 60\u0026deg;C for 15 minutes. Allowed to cool, filtered through Whatmann-42 filter paper and analyzed in AAS\u003c/p\u003e \u003cp\u003e \u003cb\u003eFish\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDried tissues were digested in conc. HNO\u003csub\u003e3\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e at 1:1 ratio in microwave digestion system at 130\u0026deg;C, diluted with Milli Q water and filtered with Whatman filter paper number 42. The samples were further diluted with Milli Q water for analysis.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Instrument\u003c/h2\u003e \u003cp\u003eA Perkin Elmer, PinAAcle Atomic Absorption Apectrometer (AAS) with Zeeman background correction system equipped with a flame furnace was used to measure Mn, Pb, Cd and Cr in the samples using an external standard method. Detection limit of the instrument was 0.127 mg/L for Mn, 0.18 mg/L for Pb, 0.052 mg/L for Cd and 0.096 mg/L for Cr.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1. Quality assurance and quality control (QA/QC):\u003c/h2\u003e \u003cp\u003eThe quality assurance and quality control (QA/QC) Analytical estimation was performed using NIST traceable Certified Reference Material of Multielement standard with purity of more than 99.99%. The Atomic Absorption Spectrometer (AAS), Perkin Elmer, PinAAcle 900F was calibrated with three-point calibration in triplicate. The sample were analyzed in triplicate with a mandatory blank sample for all the estimations during study. The QA/QC data is depicted in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQA/QC results of analytical methods for heavy metal concentrations.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDetection Limit, mg/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRecovery, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRSD*, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.127\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e103.8-106.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.180\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e93.6-106.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e10.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.052\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95.6-108.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.096\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e88.4-105.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e13.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003e*Relative Standard Deviation\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Experimental analysis\u003c/h2\u003e \u003cp\u003eHeavy metals concentration in water sample from river Ganga was calculated by the formula given below:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\mathbf{H}\\mathbf{e}\\mathbf{a}\\mathbf{v}\\mathbf{y} \\mathbf{m}\\mathbf{e}\\mathbf{t}\\mathbf{a}\\mathbf{l} \\mathbf{c}\\mathbf{o}\\mathbf{n}\\mathbf{c}\\mathbf{e}\\mathbf{n}\\mathbf{t}\\mathbf{r}\\mathbf{a}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n}=\\frac{\\mathbf{A}\\mathbf{A}\\mathbf{S} \\mathbf{r}\\mathbf{e}\\mathbf{a}\\mathbf{d}\\mathbf{i}\\mathbf{n}\\mathbf{g}}{\\mathbf{V}\\mathbf{o}\\mathbf{l}\\mathbf{u}\\mathbf{m}\\mathbf{e} \\mathbf{o}\\mathbf{f} \\mathbf{t}\\mathbf{h}\\mathbf{e} \\mathbf{s}\\mathbf{a}\\mathbf{m}\\mathbf{p}\\mathbf{l}\\mathbf{e}}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(Eq.\u0026nbsp;2)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn fishes, the concentration of heavy metals in fish tissue was calculated as:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\mathbf{H}\\mathbf{e}\\mathbf{a}\\mathbf{v}\\mathbf{y} \\mathbf{m}\\mathbf{e}\\mathbf{t}\\mathbf{a}\\mathbf{l} \\mathbf{c}\\mathbf{o}\\mathbf{n}\\mathbf{c}\\mathbf{e}\\mathbf{n}\\mathbf{t}\\mathbf{r}\\mathbf{a}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n}=\\frac{\\mathbf{A}\\mathbf{A}\\mathbf{S} \\mathbf{r}\\mathbf{e}\\mathbf{a}\\mathbf{d}\\mathbf{i}\\mathbf{n}\\mathbf{g}}{\\begin{array}{c}weight of the sample \\left(\\mathbf{g}\\mathbf{m}\\right)\\\\ \\end{array}}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(Eq.\u0026nbsp;3)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Bioaccumulation factor\u003c/h2\u003e \u003cp\u003eBio concentration factor is the ratio of the contaminant in an organism to the concentration in the ambient environment in the steady state, where the organism can take in the contaminant through ingestion with its food as well as through direct contact. BCF was calculated using the formula suggested by (Lau et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\mathbf{B}\\mathbf{i}\\mathbf{o}\\mathbf{a}\\mathbf{c}\\mathbf{c}\\mathbf{u}\\mathbf{m}\\mathbf{u}\\mathbf{l}\\mathbf{a}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n} \\mathbf{f}\\mathbf{a}\\mathbf{c}\\mathbf{t}\\mathbf{o}\\mathbf{r}=\\frac{\\mathbf{C}\\mathbf{o}\\mathbf{n}\\mathbf{c}\\mathbf{e}\\mathbf{n}\\mathbf{t}\\mathbf{r}\\mathbf{a}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n} \\mathbf{o}\\mathbf{f} \\mathbf{h}\\mathbf{e}\\mathbf{a}\\mathbf{v}\\mathbf{y} \\mathbf{m}\\mathbf{e}\\mathbf{t}\\mathbf{a}\\mathbf{l}\\mathbf{s} \\mathbf{i}\\mathbf{n} \\mathbf{f}\\mathbf{i}\\mathbf{s}\\mathbf{h} \\mathbf{t}\\mathbf{i}\\mathbf{s}\\mathbf{s}\\mathbf{u}\\mathbf{e}}{\\mathbf{C}\\mathbf{o}\\mathbf{n}\\mathbf{c}\\mathbf{e}\\mathbf{n}\\mathbf{t}\\mathbf{r}\\mathbf{a}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n} \\mathbf{o}\\mathbf{f} \\mathbf{h}\\mathbf{e}\\mathbf{a}\\mathbf{v}\\mathbf{y} \\mathbf{m}\\mathbf{e}\\mathbf{t}\\mathbf{a}\\mathbf{l}\\mathbf{s} \\mathbf{i}\\mathbf{n} \\mathbf{s}\\mathbf{u}\\mathbf{r}\\mathbf{r}\\mathbf{o}\\mathbf{u}\\mathbf{n}\\mathbf{d}\\mathbf{i}\\mathbf{n}\\mathbf{g} \\mathbf{w}\\mathbf{a}\\mathbf{t}\\mathbf{e}\\mathbf{r}}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(Eq.\u0026nbsp;4)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Estimated daily intake\u003c/h2\u003e \u003cp\u003eFish muscles are the major source of food for 50% of the human population. Therefore, fish muscles are used for calculating the human health risk through an estimated daily intake (EDI) of metals. Estimated daily intake (EDI) is calculated by the following equation as per (Song et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\text{E}\\text{D}\\text{I} (\\text{m}\\text{g}/\\text{k}\\text{g} \\text{b}\\text{o}\\text{d}\\text{y} \\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{c}\\text{o}\\text{n}\\text{s}\\text{u}\\text{m}\\text{e}\\text{r}/\\text{d}\\text{a}\\text{y}) =\\frac{\\left(\\text{C}\\text{o}\\text{n}\\text{c}\\text{e}\\text{n}\\text{t}\\text{r}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n} \\text{o}\\text{f} \\text{m}\\text{e}\\text{t}\\text{a}\\text{l} \\text{x} \\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{f}\\text{i}\\text{s}\\text{h} \\text{c}\\text{o}\\text{n}\\text{s}\\text{u}\\text{m}\\text{e}\\text{d} \\text{p}\\text{e}\\text{r} \\text{d}\\text{a}\\text{y}\\right)}{\\text{B}\\text{o}\\text{d}\\text{y} \\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{c}\\text{o}\\text{n}\\text{s}\\text{u}\\text{m}\\text{e}\\text{r}}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(Eq.\u0026nbsp;5)\u003c/b\u003e \u003c/p\u003e \u003cp\u003ewhere, the concentration of metals in muscles was converted into dry weight by dividing with a concentration factor 4.8.as per (Rahman et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The average weight of fish consumed per day is 25g as suggested by a North India survey study by (Kumar et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and average body weight of consumer is 52 for Indian men (Jain et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Dang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1996\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Human health risk assessment\u003c/h2\u003e \u003cp\u003eHeavy metal accumulation in a food chain is one of the risk factors for human health. Some metals adversely affect the nervous system (Briffa et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and many are reported to be carcinogenic (Faroon et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This study will be a pioneer for neurotoxic risk of heavy metals through the consumption of the common fishes. In order to assess the risk due to consumption of metal-loaded fishes, we calculated estimated daily intake (EDI) (Song et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), target hazard quotient (THQ) and hazard index (HI) which gives an account of potential risk on health due to heavy metals consumption through contaminated food (Chary et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hough et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and calculated as\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\mathbf{T}\\mathbf{H}\\mathbf{Q}=\\frac{\\mathbf{E}\\mathbf{D}\\mathbf{I}}{\\mathbf{R}\\mathbf{f}\\mathbf{D}}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(Eq.\u0026nbsp;6)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWhere EDI is calculated as per Eq.\u0026nbsp;5. RfD is the standard dose intake of a particular metal in a day (mg/kg body weight/day) that is under tolerable and healthy range (USEPA, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), given in table no 8. A THQ more than 1 indicates deleterious health effect due to contaminated food exposure in the population.\u003c/p\u003e \u003cp\u003eHI indicates risk due to multiple metals present in contaminated food and calculated as:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\mathbf{H}\\mathbf{I}=\\sum \\mathbf{T}\\mathbf{H}\\mathbf{Q}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(Eq.\u0026nbsp;7)\u003c/b\u003e (USEPA, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2011\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Statistical analysis:\u003c/h2\u003e \u003cp\u003eThe significant difference between heavy metal contamination at different sampling sites were compared using one way anova. The significant difference between concentration of heavy metals and their bioaccumulation in various fish tissues were compared using Two Way Anova test and correlation test was done by Pearson\u0026rsquo;s correlation matrix to show the inter elemental relation.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results And Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Analysis of physicochemical properties of water in Varanasi\u003c/h2\u003e \u003cp\u003eThe physicochemical qualities of river water samples gathered from ten different sites of Varanasi are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The temperature of the river water in the studied period ranged from 18 to 30\u0026deg;C with an average temperature of 27\u0026deg;C. This result was stable over time. The pH value observed indicates lower pH towards the drainage site than other river sites, indicating acidic water quality towards the drain, which may be due to more CO\u003csub\u003e2\u003c/sub\u003e. The solubility of metal ions in water also has an impact on pH (Sener et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Osibanjo et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) where lower pH indicates higher solubility and vice versa. Although higher average pH (9.6) in the Varanasi district was observed indicating alkaline nature due to the presence of weak acid and strong bases like carbonates, bicarbonates, and hydroxides in the water body (Maurya et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Alkalinity of water increases on pollution load from upstream to downstream, say from Kanpur to Varanasi (Gupta et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Although Ganga water holds buffering capacity, nevertheless this pH is unsuitable for human consumption as well as for the healthy survival of fishes. However, according to European Union, fisheries and aquatic life 6.0 to 9.0 pH limits is recommended (USEPA, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; USEPA, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1999a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDissolved Oxygen determines the purity of water and life within the water body. The observed DO is below the permissible limit at the drainage site and within range at other river sites, indicating highly impure water at the drainage site due to heavy sewage discharge from the city. Aquatic aerobic bacteria consume oxygen from water for the decomposition of wastes, thus increasing biological oxygen demand (BOD). In the present study, average BOD was measured at 53.77 mg/L at the drainage site (Table.2) showing high organic pollution which may be due to untreated domestic sewage, agriculture runoff, and residual fertilizers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Heavy metal analysis in water\u003c/h2\u003e \u003cp\u003eThe heavy metals concentrations in the ten selected sites are recorded and presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Concentration of Pb, Mn, Cd and Cr were recorded highest at Varuna Ganga confluence point followed by Nagwa and Raj ghat. These points are noted to have highest sewage discharge from the city and are considered among drainage sites. The highest Lead (Pb) concentration was recorded 1.297 mg/L which was much above than the permissible limits stated by Environment protection agency (EPA). (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e Similarly, Mn, Cr and Cd were also reported above the permissible range. Similar study was conducted at Kanpur, Allahabad, Mirzapur and Varanasi districts of Uttar Pradesh and observed that river Ganga water loaded with Pb 0.24 mg/l, Cd 0.85 mg/l and Cr 0.45 mg/l concentrations in Varanasi in 2019 (Maurya et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These metal contamination were statistically significant at different sampling sites with p\u0026thinsp;\u0026lt;\u0026thinsp;0.5. The interaction of heavy metals with water, sediment and aquatic lives is responsible for their transport in the environment (Sarkar et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The results of the present study indicated that, industrial effluent discharge and agricultural runoff, released into the Ganga River in Varanasi is polluted with heavy metals and unfit for human consumption. Accumulation of these persistent pollutants may cause huge risk for the fish and human consuming edible fishes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eShowing heavy metal contamination in mg/L at different sampling sites. Statistical significance of heavy metal contamination at different sampling sites was done using One Way Anova and the differences were significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.5, f\u0026thinsp;=\u0026thinsp;1.6309\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSites\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePermissible limit as per EPA\u003c/b\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.05 mg/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.05 mg/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.1 mg/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005 mg/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNagwa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.093\u0026thinsp;\u0026plusmn;\u0026thinsp;0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.221\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.164\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.156\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSamne ghat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.477\u0026thinsp;\u0026plusmn;\u0026thinsp;0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.200\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.146\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.131\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssi ghat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.140\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.141\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.144\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.130\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTulsi ghat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.017\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.128\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.140\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.124\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHarishchandra ghat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.158\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.153\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.157\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.155\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShivala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.075\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.143\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.143\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.123\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDassaswamedh ghat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.146\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.193\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.147\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.140\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManikarnika ghat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.181\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.175\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.156\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.152\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaj ghat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.281\u0026thinsp;\u0026plusmn;\u0026thinsp;0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.181\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.153\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.153\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaruna ganga confluence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.297\u0026thinsp;\u0026plusmn;\u0026thinsp;0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.325\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.169\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.161\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*\u003cb\u003eEPA: Environment Protection Agency (\u003c/b\u003eFEPA, 2003).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Analysis of heavy metals in fish tissues.\u003c/h2\u003e \u003cp\u003eThe collected fish tissue samples of gills, liver and muscles were estimated for the accumulation of heavy metals (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In all the seven fish species, the degree of heavy metal concentration followed liver\u0026thinsp;\u0026gt;\u0026thinsp;gills\u0026thinsp;\u0026gt;\u0026thinsp;muscles. Liver being an important organ for detoxification as well as for protein synthesis may be a possible reason for having the highest metal affinity (Fernandes et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Gills have a large surface area, and are in continuous contact with the aquatic environment, therefore are the second most important site for metal concentration. Another reason may be due to the increased number of chloride cells that pick up metal ions from contaminated water (Mazon et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Costa et al., 2002). Although fish muscles are consumed as protein source all over the globe, it is a metabolically less active tissue (Adhikari et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Radhakrishnan, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and the reason for least accumulation of metals in muscles. Less extensive blood circulation in muscles in comparison to other vital organs like liver, kidney and gills is also a major factor. The heavy metal trend was Mn\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Cd in almost all the species and tissues. Probable reason for more Mn concentration could be cumulative role of water contamination and essential elemental nature of Mn in enzymatic activity (Altaf et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Cr enters the aquatic system via multiple industrial sources (Ghosh, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Bagchi et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) from where Hexavalent form of chromium is reported to diffuses readily in the fish tissue and penetrates cell membrane (Ahmed et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Few previous results show Cd and Pb were more than Cr in fish tissue (Maurya et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ghosh, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Javed et al., 2013; Begum et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, the highest concentration Pb was observed in \u003cem\u003eCarpio\u003c/em\u003e liver (8.86 \u0026micro;g/g) and lowest in Baikari muscles (0.07 \u0026micro;g/g). The FAO proposed a limit of 0.5 \u0026micro;g/g for Pb in food (FAO, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) while FEPA (Food and Environment Protection Act) set this value to 2.0 \u0026micro;g/g (FEPA, 2003). Mn was recorded highest in Pathari liver (53.19 \u0026micro;g/g) and lowest in Baikari muscles (1.10 \u0026micro;g/g). Cr was estimated highest in Pathari liver whereas lowest in Bam muscles. European Union Commission (EUC) suggested the daily tolerable chromium concentration to be 1 \u0026micro;g/g, while the FEPA suggested 0.15 \u0026micro;g/g and WHO suggested 0.15 \u0026micro;g/g (FEPA, 2003). Cadmium (Cd) is a severe pollutant and an extremely noxious element, transported in water. Different industrial and domestic channels induced in the Ganga River may be the source of Cd contamination.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConcentration of heavy metals in different fish tissue (\u0026micro;g/g) and their permissible range by FAO. Statistical significance of heavy metal concentration in various fish tissues was done using two way Anova test and the differences were significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, F \u003csub\u003etissue\u003c/sub\u003e = 10.144, F \u003csub\u003emetals\u003c/sub\u003e 14.339 and F \u003csub\u003etissue X Metals\u003c/sub\u003e = 2.312.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTissue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePermissible Limit as per FAO\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.2 \u0026micro;g/g\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.98 \u0026micro;g/g\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.05 \u0026micro;g/g\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.02 \u0026micro;g/g\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSauri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.905\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.829\u0026thinsp;\u0026plusmn;\u0026thinsp;0.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.046\u0026thinsp;\u0026plusmn;\u0026thinsp;0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.427\u0026thinsp;\u0026plusmn;\u0026thinsp;0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.248\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.858\u0026thinsp;\u0026plusmn;\u0026thinsp;0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.978\u0026thinsp;\u0026plusmn;\u0026thinsp;0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.452\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.778\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.419\u0026thinsp;\u0026plusmn;\u0026thinsp;0.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.896\u0026thinsp;\u0026plusmn;\u0026thinsp;0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.275\u0026thinsp;\u0026plusmn;\u0026thinsp;0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaikari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.284\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.129\u0026thinsp;\u0026plusmn;\u0026thinsp;0.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.165\u0026thinsp;\u0026plusmn;\u0026thinsp;0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.075\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.449\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.328\u0026thinsp;\u0026plusmn;\u0026thinsp;0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.706\u0026thinsp;\u0026plusmn;\u0026thinsp;0.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.120\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.079\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.106\u0026thinsp;\u0026plusmn;\u0026thinsp;0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.145\u0026thinsp;\u0026plusmn;\u0026thinsp;0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.025\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarpio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.146\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.842\u0026thinsp;\u0026plusmn;\u0026thinsp;0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.115\u0026thinsp;\u0026plusmn;\u0026thinsp;0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.906\u0026thinsp;\u0026plusmn;\u0026thinsp;0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.868\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.614\u0026thinsp;\u0026plusmn;\u0026thinsp;0.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.704\u0026thinsp;\u0026plusmn;\u0026thinsp;1.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.274\u0026thinsp;\u0026plusmn;\u0026thinsp;0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.316\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.157\u0026thinsp;\u0026plusmn;\u0026thinsp;0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.993\u0026thinsp;\u0026plusmn;\u0026thinsp;0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.487\u0026thinsp;\u0026plusmn;\u0026thinsp;0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTilapia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.876\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.872\u0026thinsp;\u0026plusmn;\u0026thinsp;0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.094\u0026thinsp;\u0026plusmn;\u0026thinsp;0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.143\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.025\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.432\u0026thinsp;\u0026plusmn;\u0026thinsp;0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.845\u0026thinsp;\u0026plusmn;\u0026thinsp;0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.158\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.784\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7380\u0026thinsp;\u0026plusmn;\u0026thinsp;0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.363\u0026thinsp;\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.129\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTengra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.435\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.344\u0026thinsp;\u0026plusmn;\u0026thinsp;0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.689\u0026thinsp;\u0026plusmn;\u0026thinsp;0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.681\u0026thinsp;\u0026plusmn;\u0026thinsp;0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.920\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.166\u0026thinsp;\u0026plusmn;\u0026thinsp;0.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.371\u0026thinsp;\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.614\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.766\u0026thinsp;\u0026plusmn;\u0026thinsp;0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.281\u0026thinsp;\u0026plusmn;\u0026thinsp;0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.342\u0026thinsp;\u0026plusmn;\u0026thinsp;0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.884\u0026thinsp;\u0026plusmn;\u0026thinsp;0.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.656\u0026thinsp;\u0026plusmn;\u0026thinsp;0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.651\u0026thinsp;\u0026plusmn;\u0026thinsp;0.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.076\u0026thinsp;\u0026plusmn;\u0026thinsp;1.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.467\u0026thinsp;\u0026plusmn;\u0026thinsp;0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.684\u0026thinsp;\u0026plusmn;\u0026thinsp;0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.513\u0026thinsp;\u0026plusmn;\u0026thinsp;0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.489\u0026thinsp;\u0026plusmn;\u0026thinsp;0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.904\u0026thinsp;\u0026plusmn;\u0026thinsp;0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.425\u0026thinsp;\u0026plusmn;\u0026thinsp;1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.577\u0026thinsp;\u0026plusmn;\u0026thinsp;0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.354\u0026thinsp;\u0026plusmn;\u0026thinsp;0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.193\u0026thinsp;\u0026plusmn;\u0026thinsp;2.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.467\u0026thinsp;\u0026plusmn;\u0026thinsp;1.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.886\u0026thinsp;\u0026plusmn;\u0026thinsp;0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.288\u0026thinsp;\u0026plusmn;\u0026thinsp;0.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.701\u0026thinsp;\u0026plusmn;\u0026thinsp;0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003e*FAO: Food and Agriculture Organisation (\u003c/b\u003eFAO, 2022).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHighest Cd was recorded in Carpio liver (3.27 \u0026micro;g/g) and remains undetected in tengra, bam and pathari. Carpio is larger in size, so its higher biomass can be considered for higher accumulation of metals. However small size of pathari fish gains importance because smaller body size reduces the metal accumulation through surface action. Our study observed 0.158 \u0026micro;g/g Cd in Tilapia liver. The concentration level of each metal in fish tissue was statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. In similar Egyptian studies in Lake Nasser, the liver of O. niloticus was reported with 1.38 mg/kg dry weigh Cd whereas it remained undetected in fish tissues from Wadi Al-Rayan Lake (Sally et al., 2020; Dalia et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Whereas the lesser accumulation in Tengra was observed in previous study (Maurya et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Variation of heavy metal concentration in fish tissues may be due to metal contamination in the surrounding water in which fish travels. Age is also another important factor because time they spend in water decide the concentration of metals in their body since fishes were captured at their different life period. Similar study was done where Cd was accumulated highest in liver tissue of bottom feeder followed by column and surface feeder fishes (Kumar et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Different concentration of heavy metals in different fish species might be the result of different ecological needs, metabolism and feeding habit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.4\u003c/b\u003e. \u003cb\u003eCorrelation analysis of heavy metal in fish tissue\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eInter elemental relation is shown by Pearson's correlation matrix (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The correlation coefficient ranges between \u0026minus;\u0026thinsp;1 to +\u0026thinsp;1. A positive correlation between two variable means for every positive increase in one variable, there is a positive increase of a fixed proportion in the other,while a negative correlation indicates that for every positive increase in one variable, there is a negative decrease of a fixed proportion in the other. In our study, we found notable correlation between Pb and Cd (r\u0026thinsp;=\u0026thinsp;0.72, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eShows inter elemental relation through Pearson's correlation matrix.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy metals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.2414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe probable reason is due to the high concentration of these two elements in Carpio and Tengra in the all the selected fish organs. Cd and Pb was reported to occur in leaded petrol, coal cumbustion, smelting and old pre industrial lead. Accumulation of Cd and Pb by C. catla and C. mrigala had already been observed in other studies (Dhanakumar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The negative correlation was calculated in case of Cd and Mn, while in case of Pb to Mn, Pd to Cr, Mn to Cr, and Cr to Cd, there were non-significant positive correlations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Determination of bio-accumulation factor\u003c/h2\u003e \u003cp\u003eFor studying ecological risk assessment, Bio accumulation factor (BAF) is studied to know the concentration of heavy metals transferred from water dwelling organism from the surrounding water. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, BAF in each fish species followed the same trend in organs liver\u0026thinsp;\u0026gt;\u0026thinsp;gills\u0026thinsp;\u0026gt;\u0026thinsp;muscles and all metals had tissue concentrations higher than their corresponding concentrations in water. Bioaccumulation of heavy metals in fish tissues, as well as between four metals were statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 .This report was supported by other studies in different fish species and different water bodies where accumulation of HM in fishes showed a site dependent response (Maurya et al., 2018; Elhaddad et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Olaifa et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows bio concentration factor of all the four metals in each fish. This is because metabolically active tissues show higher BAF than other less active tissues like muscles (Chale, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBio-accumulation factor in different fish tissues. Statistical significance of heavy metal accumulation in various fish tissues was done using two way Anova test and the differences were significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, F\u003csub\u003etissue\u003c/sub\u003e = 9.052, F\u003csub\u003emetals\u003c/sub\u003e = 10.82 and F\u003csub\u003etissue X Metals\u003c/sub\u003e = 2.2664.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTissue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSauri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.506\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.676\u0026thinsp;\u0026plusmn;\u0026thinsp;3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.417\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.985\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.392\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.924\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.083\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.160\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.178\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.356\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.987\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.928\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaikari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.318\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.749\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.752\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.530\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.744\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.458\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.295\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.842\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.205\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.950\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.620\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.178\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarpio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.714\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.578\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.535\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.324\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.914\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.765\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e168.506\u0026thinsp;\u0026plusmn;\u0026thinsp;8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.887\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.985\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.276\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.735\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.391\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTilapia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.015\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.543\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.620\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.999\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.984\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.116\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.545\u0026thinsp;\u0026plusmn;\u0026thinsp;3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.107\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.026\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.207\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.491\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.905\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTengra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.626\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.657\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.076\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.764\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.464\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.451\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.544\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.587\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.308\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.401\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.803\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.874\u0026thinsp;\u0026plusmn;\u0026thinsp;3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.523\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.7683\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.988\u0026thinsp;\u0026plusmn;\u0026thinsp;4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.841\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.352\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.548\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.209\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.254\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.805\u0026thinsp;\u0026plusmn;\u0026thinsp;4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.897\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e189.97\u0026thinsp;\u0026plusmn;\u0026thinsp;9.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e193.176\u0026thinsp;\u0026plusmn;\u0026thinsp;9.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.873\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.457\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.594\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.6\u003c/b\u003e. \u003cb\u003eHealth risk assessment.\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe water quality of river Ganga is degraded due to heavy metals contamination as shown by our study and this can impact human health by direct consumption or contaminated fishes captured from river Ganga. The Estimated Daily Intake of different metals via all the collected fishes are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The EDI for Pb was measured higher than the recommended daily allowance in Sauri, Carpio, Bam and Pathari. Mn was higher in Sauri and Baikari. EDI for Cr was higher than the recommended daily allowance in all the species. While Cd was higher in Sauri, Tilapia and Carpio..\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eShowing Estimated daily intake (EDI), Recommended dose (RfD) established by USEPA (USEPA. 1999a) Target Hazard Quotient (THQ), Hazard index (HI).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeavy metals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRecommended daily allowance mg day-\u003csup\u003e1\u003c/sup\u003e kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e body weight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRfD\u003c/p\u003e \u003cp\u003emg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEDI\u003c/p\u003e \u003cp\u003emg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTHQ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSauri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003cp\u003eMn\u003c/p\u003e \u003cp\u003eCr\u003c/p\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e2.5-3\u003c/p\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.140\u003c/p\u003e \u003cp\u003e1.500\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003cp\u003e4.444\u003c/p\u003e \u003cp\u003e1.902\u003c/p\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003cp\u003e0.031\u003c/p\u003e \u003cp\u003e0.012\u003c/p\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaikari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003cp\u003eMn\u003c/p\u003e \u003cp\u003eCr\u003c/p\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e2.5-3\u003c/p\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.140\u003c/p\u003e \u003cp\u003e1.50\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003cp\u003e0.395\u003c/p\u003e \u003cp\u003e2.066\u003c/p\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003cp\u003e0.002\u003c/p\u003e \u003cp\u003e0.013\u003c/p\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarpio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003cp\u003eMn\u003c/p\u003e \u003cp\u003eCr\u003c/p\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e2.5-3\u003c/p\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.140\u003c/p\u003e \u003cp\u003e1.500\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003cp\u003e1.129\u003c/p\u003e \u003cp\u003e3.280\u003c/p\u003e \u003cp\u003e1.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003cp\u003e0.008\u003c/p\u003e \u003cp\u003e0.021\u003c/p\u003e \u003cp\u003e1.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTilapia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003cp\u003eMn\u003c/p\u003e \u003cp\u003eCr\u003c/p\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e2.5-3\u003c/p\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.14\u003c/p\u003e \u003cp\u003e1.500\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003cp\u003e0.622\u003c/p\u003e \u003cp\u003e1.552\u003c/p\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.010\u003c/p\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTengra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003cp\u003eMn\u003c/p\u003e \u003cp\u003eCr\u003c/p\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e2.5-3\u003c/p\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.140\u003c/p\u003e \u003cp\u003e1.500\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003cp\u003e0.632\u003c/p\u003e \u003cp\u003e0.841\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.005\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003cp\u003eMn\u003c/p\u003e \u003cp\u003eCr\u003c/p\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e2.5-3\u003c/p\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.14\u003c/p\u003e \u003cp\u003e1.5\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003cp\u003e1.257\u003c/p\u003e \u003cp\u003e0.321\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003cp\u003e0.008\u003c/p\u003e \u003cp\u003e0.002\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003cp\u003eMn\u003c/p\u003e \u003cp\u003eCr\u003c/p\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e2.5-3\u003c/p\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.140\u003c/p\u003e \u003cp\u003e1.500\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003cp\u003e2.250\u003c/p\u003e \u003cp\u003e0.460\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003cp\u003e0.016\u003c/p\u003e \u003cp\u003e0.003\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Target Hazard quotient (THQ) estimated for individual heavy metals through consumption of different fish species are presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The acceptance value for THQ is 1, therefore except Cd in Carpio, every metal was below the hazard quotient. Similar result was obtained by other studies where the muscles of fishes were within the permissible limits for human consumption, and target hazard quotient less than 1, may be an indication for less polluted water bodies (Maurya et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Ahmed et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); Ali et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Total THQ value i.e. hazard index (HI) of metals was recorded in following sequence: Carpio\u0026thinsp;\u0026gt;\u0026thinsp;Telapia\u0026thinsp;\u0026gt;\u0026thinsp;Sauri\u0026thinsp;\u0026gt;\u0026thinsp;Pathari\u0026thinsp;\u0026gt;\u0026thinsp;Bam\u0026thinsp;\u0026gt;\u0026thinsp;Tengra\u0026thinsp;\u0026gt;\u0026thinsp;Baikari. Average HI value for Carpio and Telapia was found above 1 which indicates that consumption of these contaminated fishes may lead to health hazard for human. Maximum HI was recorded in Carpio, which is among highly consumable fish by human. This demonstrates that Carpio consumption can pose health risk to human. Therefore, regular monitoring of heavy metals in fishes should be performed to prevent excessive concentration in the humans through food chain.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe outcome of present study reveals that Pb, Mn, Cr and Cd were higher than the permissible limit of international standards (BIS and WHO) (BIS, 1993; WHO, 2017) for drinking water, in river Ganga in Varanasi district, which clearly indicates that Ganga water in this place is not suitable for direct human consumption. Proper water treatment plants are required. Varuna Ganga confluence point and Samne ghat were the most polluted sites, due to which toxic metals like lead and cadmium get accumulated in aquatic lives like fishes. The accumulation is maximum in fish\u0026rsquo;s liver tissues followed by gills and muscles. Consumption of fishes contaminated with heavy metals could cause health hazard to human. Carpio rated at highest risk for human consumption. Heavy metals contamination in the fish is an alert for the responsible beings to take corrective measures for Ganga River and protect the well-being of aquatic lives and local inhabitants significantly.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAAS Atomic absorption spectrophotometer\u003c/p\u003e\u003cp\u003eBAF Bioaccumulation factor\u003c/p\u003e\u003cp\u003eEDI Estimated daily intake\u003c/p\u003e\u003cp\u003eTHQ Target hazard quotient\u003c/p\u003e\u003cp\u003eHI Hazard Index\u003c/p\u003e\u003cp\u003ePb Lead\u003c/p\u003e\u003cp\u003eMn Manganese\u003c/p\u003e\u003cp\u003eCr Chromium\u003c/p\u003e\u003cp\u003eCd Cadmium\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll authors have read, understood, and have complied as applicable with the statement on \u0026quot;Ethical responsibilities of Authors\u0026quot; as found in the Instructions for Authors and are aware that with minor exceptions, no changes can be made to authorship once the paper is submitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank CSIR-Indian Institute of Toxicology Research, Lucknow and Department of Chemical Engineering, IIT, BHU for providing the facilities required to perform this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVijay Nath Mishra is behind the idea of this study. Bhargawi Mishra has performed the material preparation, data collection and wrote the first draft of manuscript. Nasreen Ghazi Ansari has performed the experimental part. Geeta J. Gautam helped in data analysis, interpretation and finalizing the manuscript. Rajnish Chaturvedi commented on previous version of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThere is no funding agency for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical declaration\u003c/strong\u003e: This study involved collection of fishes from wild and direct processing for the estimation of heavy metals in different tissues. The study protocol was assessed and approved by the BHU ethics committee (542/GO/ReBi/S/02/CPCSEA dated 26.05.2017)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003eThe generated and analyzed datasets during the study are available per request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e \u003cstrong\u003ecompeting interests:\u003c/strong\u003e The authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e Not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e The authors declare no conflict of interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdhikari, S., Ghosh, L., Giri, B. 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Toxicol., 91, 36\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO (World Health Organization), Life expectancy at birth (m/f) estimate for Nigeria, (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO |Ten Chemicals of Major Public Health Concern. 2010. WHO\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Banaras Hindu University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ganga, heavy metals, pollution, fishes, health risk assessment, THQ","lastPublishedDoi":"10.21203/rs.3.rs-2168987/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2168987/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHeavy metal load is one of the factor causing deterioration of water quality of rivers and anthropogenic activities being the major cause. Present article is an attempt to evaluate the potential human health risks posed by four heavy metals (Pb, Mn, Cr and Cd). We have estimated the concentration of these heavy metal at different points of river Ganga as well as at confluence point of Ganga and Varuna rivers as follows: Pb 1.29 mg/L, Mn 1.325 mg/L, Cr 0.169 mg/L and Cd 0.161mg/L, which was above than the permissible limits stated by Environment protection agency EPA in drinking water. Randomly seven indigenous species of fishes were collected from the wild and were processed for checking the occurrence of these metals in the tissues such as Gills, Liver and Muscle. In all the seven selected fish species, degree of heavy metal concentration followed liver\u0026thinsp;\u0026gt;\u0026thinsp;gills\u0026thinsp;\u0026gt;\u0026thinsp;muscles. Highest accumulation of Pb was observed in \u003cem\u003eCyprinus carpio\u003c/em\u003e liver (8.86 \u0026micro;g/g) and lowest in Baikari muscles (0.07 \u0026micro;g/g). Total THQ value i.e. hazard index (HI) of metals was calculated for these fish species that are frequently consumed and the data showed HI values in following sequence: \u003cem\u003eC.carpio\u0026thinsp;\u0026gt;\u0026thinsp;O. nilotus\u0026thinsp;\u0026gt;\u0026thinsp;C.punctatus\u0026thinsp;\u0026gt;\u0026thinsp;J.coitor\u0026thinsp;\u0026gt;\u0026thinsp;M.armatus\u0026thinsp;\u0026gt;\u0026thinsp;M.tengara\u0026thinsp;\u0026gt;\u0026thinsp;Baikari\u003c/em\u003e. Average HI value for \u003cem\u003eC. carpio\u003c/em\u003e and \u003cem\u003eO. nilotus\u003c/em\u003e was found above 1 which indicates that intake of heavy metals through these species may cause health hazard for human. Maximum HI was recorded in \u003cem\u003eCarpio\u003c/em\u003e, which is highly consumed fish by human, hence may be harmful to them. These findings pose a threat to human population and hence needs regular monitoring of metals in fishes to prevent entry into food chain and its effect on the human beings.\u003c/p\u003e","manuscriptTitle":"Bioaccumulation of heavy metals in different fishes of Gangetic river system in Varanasi and its health risk assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-10-17 19:31:40","doi":"10.21203/rs.3.rs-2168987/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"69719d11-2cb5-48ef-b204-104dc3eacb27","owner":[],"postedDate":"October 17th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":16268757,"name":"Toxicology"},{"id":16268758,"name":"Animal Science"}],"tags":[],"updatedAt":"2022-11-03T15:47:56+00:00","versionOfRecord":[],"versionCreatedAt":"2022-10-17 19:31:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2168987","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2168987","identity":"rs-2168987","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}